98 Matching Annotations
- Jul 2019
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sg.inflibnet.ac.in sg.inflibnet.ac.in
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The table 6.1 gives the mixing probabilities and the associated parametricvalues fork(number of components) = 2,3, and 4. It may be noted thatthe Log likelihood value is smaller fork= 4 (the results fork= 5 , 6 etc.are not better than that fork= 4 and hence are not given here). The fourcomponents Poisson Mixture model is given in table 6.2. It may be notedthat 58% of wards may have higher incidence/relative risk and the remainingwards have lesser/lower incidence for the Cancer disease. We computed theposterior probability for each component for each ward (see table 6.3). Eachward is assigned to a particular component so that the posterior probability islarger. These results are also given in table 6.3 Finally we present Choroplethmaps based on those results
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The Posterior Probability of Mixing Dis-tribution
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Algorithm
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EM Procedure
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Poisson Mixture
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Data Sources
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Poisson Mixtures Distribution
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sg.inflibnet.ac.in sg.inflibnet.ac.in
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Poisson Model
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We have analysed the Cancer data of patients in 155 wards of Chennai Cor-poration by the above described method. As preliminary analyses, we havecreated the Choropleth maps for Observed counts, Population of wards, ex-pected counts for patients and SMR's.The Choropleth map for the observed counts Figure 5.2 does not show anypattern. But the Choropleth map for the expected counts Figure: 5.4 indi-cate that the inner regions of the Chennai Corporations have lower expectedcounts and the regions along the border have larger counts of patients. As ameasure of spatial heterogeneity we have computed PSH= 0:7108:Hence ofthe total spatial random variation, nearly 71% is due to spatial heterogene-ity and the remaining 28:92% is due to Poisson variation. Thus the spatialvariation is present in the data.The Choropleth map for Empirical Bayes smoothed rates Figure 5.5 re-veals that only 13 sub regions have high risk values. The wards with numbers53, 64, 67, 70, 78, 93, 100, 103, 110, 117, 122, 147 and 151 have high riskvalues. Though this information could be used by the health managers toconcentrate their work on these regions, one can look for additional covariatesin these regions for further study
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Empirical Bayesian Smoothing
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Incidence Rate and SMR
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Spatial Analysis of Cancer PatientCount Data
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sg.inflibnet.ac.in sg.inflibnet.ac.in
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Madurai Kamraj University
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Selvi, P Vetri
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Statistical spatial modelling and analysis of disease count data
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sg.inflibnet.ac.in sg.inflibnet.ac.in
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Haemocyte morphogenesis
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Spreading inhibitory behavior
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Inhibition of haemocyte aggregation
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Haemolymph protein profile
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Total haemocyte count assay
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Immunomodulatory
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Helicoverpa armiger
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Spodoptera litura
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Gut enzyme profile
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Insecticidal activity
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. Statistical analysis
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Inhibition of haemocytes spreading behavior
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. Inhibition of haemocytes aggregation behavior
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Haemolymph protein profiling
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Total haemocyte count (THC)
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Haemolymph collection
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Immunomodulatory
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Lactate dehydrogenase
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Asparate (AAT) and Alanine aminotransferase (ALT)
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Gut enzyme profile
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Oral toxicity bioassay
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Microinjection bioassay
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VS preparation
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Insect collection
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INSECTICIDAL AND IMMUNOMODULATORY ACTIVITY AGAINST INSECT PEST
Tags
- ex-3-md-2
- ex-3
- ex-3-re-3-re-5
- ex-3-re-3-re-2
- ex-3-re-3-re-3
- ex-3-re-3
- ex-3-md-7
- ex-3-md-6
- ex-3-md-5
- ex-3-re-2-re-1
- ex-3-re-1
- ex-3-md-6-md-1-md-4
- ex-3-re-2-re-2
- ex-3-re-3-re-1
- ex-3-md-6-md-1-md-1
- ex-3-md-5-md-1
- ex-3-md-6-md-1-md-2
- ex-3-md-1
- ex-3-re-3-re-4
- ex-3-md-6-md-1
- ex-3-md-6-md-1-md-3
- ex-3-md-5-md-2
- ex-3-md-3
- ex-3-re-2
- ex-3-md-4
Annotators
URL
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sg.inflibnet.ac.in sg.inflibnet.ac.in
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Utilization of VS by the prey
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Influence of prey on VS yield
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Quantification of protein of VS yielded in the prey deprivation
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Survival (SR) and venom milking rate (VMR
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Venomous saliva optimization
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Statistical analysi
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Quantification of VS for protein
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Venomous saliva utilization
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Prey type
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Starvation and collection method
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Venomous saliva optimization
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Insects Collection
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VENOMOUS SALIVA: OPTIMIZATION AND UTILIZATION
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sg.inflibnet.ac.in sg.inflibnet.ac.in
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Manonmaniam Sundaranar University
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Vinoth Kanna, A
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Rhinoceros fuscipes fab Venomous saliva biological and immunomodulatory activity against insect pest and mice
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sg.inflibnet.ac.in sg.inflibnet.ac.in
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Salivary gland-Histology
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Salivary gland-Morphology and Anatomy
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Maxillary stylet
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Mandibular stylet
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Head
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Gross morphology and histology of salivary gland
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Morphometry of head and stylet
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Head and stylet preparation
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Insect collection and maintenance
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GROSS MORPHOLOGY OF THE REDUVIID HEAD AND SALIVARY GLAND COMPLEX
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shodhganga.inflibnet.ac.in shodhganga.inflibnet.ac.in
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Statistical analysis
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Micronuclei test
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SDS -PAGE for serum protein analysis
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Estimation of serum proteins (SDS –PAGE) and Micronuclei in fish, Labeo rohita
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Estimation of bioaccumulation of trace metals inmuscle and gill tissue of fish, Labeo rohita
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Lactic dehydrogenase
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Malic dehydrogenase
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Succinic dehydrogenase
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Estimation of dehydrogenases activities (SDH, MDHand LDH) in muscle and gill tissue of fish, Labeo rohita
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Alkaline Phosphatase
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Acid Phosphatase
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Estimation of Phosphatases activities (Acid and Alkaline Phosphatase) in muscle and gill tissue of fish, Labeo rohita
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Cholesterol content
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Glycogen content
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Protein content
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Estimation of biomolecules (Protein, glycogen and cholesterol) inmuscle and gill tissue of fish, Labeo rohita
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Fish sampled from selected water bodies for further analysis
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Characteristic features ofLabeo rohita
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Animal model for the study-Labeo rohita
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Analysis of Physico-chemical parameters of the water sampled
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Survey of lakes to check their status of pollution
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sg.inflibnet.ac.in sg.inflibnet.ac.in
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Bangalore University
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Nazima Noor
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Metabolic responses of labeo rohita reared in selected lakes of Bangalore
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sg.inflibnet.ac.in sg.inflibnet.ac.in
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Increments in biomass:
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Residual nutrients
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Chlorophyll content in waters:
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Growth maximum values
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Rates of growth (OD678/day
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Growth
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Experimental Set up
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BIOMASS PRODUCTION: ROLE OF N-P CONCENTRATION AND RATIOS
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